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Objectives: Marketing authorization holder (MAH)-sponsored patient support programs (PSPs) are a major source of adverse event (AE) reports. The impact of reports from PSPs on the ability to detect AE signals is unclear. We compared signal detection performance using data from PSPs vs. non-PSP sources, and between PSPs providing clinical services vs. PSPs not providing clinical services.
Methods: Data were obtained from an internal safety database for a global pharmaceutical company 2015-2017. We assessed whether signals were detected for the reference drug-AE pairs using data from PSPs vs. non-PSP sources, and among different PSP services. The performance was evaluated by four measures including area under the receiver operating characteristic curve (AUC) and time-to-signal detection.
Results: While the majority of reports were from PSPs, non-PSP sources were better and faster at detecting signals (AUC 0.63 vs. 0.41, = 0.035; HR 3.52, = 0.014) compared to PSPs. Within PSPs, PSPs providing clinical services were marginally better at detecting signals (AUC 0.60 vs. 0.41, = 0.053) but not faster compared to PSPs not providing clinical services.
Conclusion: Reports of AEs from PSPs had worse signal detection performance compared to non-PSP sources. Pharmacovigilance experts should be mindful when using databases that contain reports from PSPs for signal detection.
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http://dx.doi.org/10.1080/14740338.2020.1792883 | DOI Listing |
IEEE J Biomed Health Inform
September 2025
Epilepsy, a highly individualized neurological disorder, affects millions globally. Electroencephalography (EEG) remains the cornerstone for seizure diagnosis, yet manual interpretation is labor-intensive and often unreliable due to the complexity of multi-channel, high-dimensional data. Traditional machine learning models often struggle with overfitting and fail in fully capturing the highdimensional, temporal dynamics of EEG signals, restricting their clinical utility.
View Article and Find Full Text PDFSmall
September 2025
School of Chemistry and Chemical Engineering, Guangxi Key Laboratory of AI-Driven Zero-Carbon Technologies, Key Laboratory of New Low-carbon Green Chemical Technology Education Department of Guangxi Zhuang Autonomous Region, Guangxi University, Nanning, 530004, China.
Sarcosine (Sar), a critical potential biomarker for prostate cancer (PCa), is primarily detected via enzyme cascade reactions involving sarcosine oxidase (SOx) and peroxidase. Nevertheless, the intermediate product hydrogen peroxide (HO) tends to diffuse to the bulk solution phase without entering subsequent reaction, leading to suboptimal detection sensitivity and compromised analytical performance. To tackle this challenge, a multilayered sandwich nanozyme cascade sensor (designated as Cu-MOF/Rf@BDC) is proposed through a confinement-mediated HO enrichment strategy.
View Article and Find Full Text PDFSmall
September 2025
Jožef Stefan Institute, Jamova cesta 39, Ljubljana, SI-1000, Slovenia.
The demand for rapid, field-deployable detection of hazardous substances has intensified the search for plasmonic sensors with both high sensitivity and fabrication simplicity. Conventional approaches to plasmonic substrates, however, often rely on lithographic precision or complex chemistries limiting scalability and reproducibility. Here, a facile, one-step synthesis of vertically aligned 2D nanosheets composed of intergrown CuO/CuO crystallites is presented, fabricated via oxygen plasma discharge on copper substrates.
View Article and Find Full Text PDFAdv Mater
September 2025
Key Laboratory of Brain-Like Neuromorphic Devices and Systems of Hebei Province, College of Electronic and Information Engineering, Hebei University, Baoding, 071002, China.
Neuromorphic Visual Devices hold considerable promise for integration into neuromorphic vision systems that combine sensing, memory, and computing. This potential arises from their synergistic benefits in optical signal detection and neuro-inspired computational processes. However, current devices face challenges such as insufficient light/dark resistance ratios, mismatched transient photo-response, and volatile retention characteristics, limiting their adaptability to complex artificial vision systems.
View Article and Find Full Text PDFAnal Methods
September 2025
Key Laboratory of Biorheological Science and Technology of Ministry of Education, College of Bioengineering, Chongqing University, Chongqing 400044, P. R. China.
Aflatoxin B1 (AFB1) is one of the most toxic mycotoxins that pose great health threats to humans. Herein, an aptasensor-based fluorescent signal amplification strategy is developed for the detection of AFB1. Initially, the AFB1 aptamers labelled with carboxyfluorescein (FAM) are adsorbed onto graphene oxide (GO), triggering energy transfer.
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